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lysandre
updated
a
dataset
about 16 hours ago
Post
754
As you might have already heard, FLUX.1-Kontext-dev is now released and taken the generative community by storm!
In case you haven't come across it, you can get started with Kontext using 🤗 diffusers. See the official [model]( black-forest-labs/FLUX.1-Kontext-dev) and [docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux#flux).
Want to know how inference companies like Fal & Replicate are able to run the model so fast and in under 2 seconds per image? Check out this [gist](https://gist.github.com/a-r-r-o-w/d08c37e8bd3e9c26b4ce80360be148c6) for some details!
In case you haven't come across it, you can get started with Kontext using 🤗 diffusers. See the official [model]( black-forest-labs/FLUX.1-Kontext-dev) and [docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux#flux).
Want to know how inference companies like Fal & Replicate are able to run the model so fast and in under 2 seconds per image? Check out this [gist](https://gist.github.com/a-r-r-o-w/d08c37e8bd3e9c26b4ce80360be148c6) for some details!
- 1 reply
Update `deploy-large-language-models/` images and add `request-to-add.png`
#512 opened about 18 hours ago
by
alvarobartt
Post
844
Hunyuan-A13B 🔥 New MoE LLM by TencentHunyuan
tencent/Hunyuan-A13B-Instruct
✨80B total / 13B active params
✨256K context window
✨Dual-mode reasoning: fast & slow thinking
✨Efficient inference (GQA + quantization)
tencent/Hunyuan-A13B-Instruct
✨80B total / 13B active params
✨256K context window
✨Dual-mode reasoning: fast & slow thinking
✨Efficient inference (GQA + quantization)
hynky
authored
a
paper
about 19 hours ago
guipenedo
authored
a
paper
about 19 hours ago
jeffboudier
updated
a
Space
1 day ago
ariG23498
updated
a
dataset
1 day ago
Post
334
Dataset Viewer for PDFs just landed on Hugging Face 📖🤗 you can now preview all the PDFs easier than before!
on top of this, there's PdfFolder format to load the PDF datasets quicker 💨
> to use it, your dataset should follow a directory format like folder/train/doc1.pdf, folder/train/doc1.pdf
> if you want to include bounding boxes, labels etc. you can keep them in a metadata.csv file in the same folder 🤝
read document dataset docs https://huggingface.co/docs/datasets/main/en/document_dataset
check all the document datasets here https://huggingface.co/datasets?modality=modality:document&sort=trending 📖
on top of this, there's PdfFolder format to load the PDF datasets quicker 💨
> to use it, your dataset should follow a directory format like folder/train/doc1.pdf, folder/train/doc1.pdf
> if you want to include bounding boxes, labels etc. you can keep them in a metadata.csv file in the same folder 🤝
read document dataset docs https://huggingface.co/docs/datasets/main/en/document_dataset
check all the document datasets here https://huggingface.co/datasets?modality=modality:document&sort=trending 📖
freddyaboulton
posted
an
update
3 days ago
Post
1531
LongWriter-Zero 🔥 A Purely RL trained LLM handles 10K+ token coherent passages by Tsinghua University
Model:
THU-KEG/LongWriter-Zero-32B
Dataset:
THU-KEG/LongWriter-Zero-RLData
Paper:
LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning (2506.18841)
✨ 32B
✨ Multi-reward GRPO: length, fluency, structure, non-redundancy
✨ Enforces <think><answer> format via Format RM
✨ Build on Qwen2.5-32B-base
Model:
THU-KEG/LongWriter-Zero-32B
Dataset:
THU-KEG/LongWriter-Zero-RLData
Paper:
LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning (2506.18841)
✨ 32B
✨ Multi-reward GRPO: length, fluency, structure, non-redundancy
✨ Enforces <think><answer> format via Format RM
✨ Build on Qwen2.5-32B-base
Post
244
MOSS-TTSD 🔊 Bilingual text-to-spoken dialogue model by Fudan University - Open MOSS team.
Model:
fnlp/MOSS-TTSD-v0
Demo:
fnlp/MOSS-TTSD
✨ Supports Chinese & English
✨ Zero-shot 2-speaker voice cloning
✨ Long-form generation (up to 960s)
✨ Built on Qwen 3
Model:
fnlp/MOSS-TTSD-v0
Demo:
fnlp/MOSS-TTSD
✨ Supports Chinese & English
✨ Zero-shot 2-speaker voice cloning
✨ Long-form generation (up to 960s)
✨ Built on Qwen 3
Post
3080
Hackathons in Paris on July 5th and 6th!
Hugging Face just wrapped 4 months of deep work with AMD to push kernel-level optimization on their MI300X GPUs. Now, it's time to share everything we learned.
Join us in Paris at STATION F for a hands-on weekend of workshops and a hackathon focused on making open-source LLMs faster and more efficient on AMD.
Prizes, amazing host speakers, ... if you want more details, navigate to https://lu.ma/fmvdjmur!
Hugging Face just wrapped 4 months of deep work with AMD to push kernel-level optimization on their MI300X GPUs. Now, it's time to share everything we learned.
Join us in Paris at STATION F for a hands-on weekend of workshops and a hackathon focused on making open-source LLMs faster and more efficient on AMD.
Prizes, amazing host speakers, ... if you want more details, navigate to https://lu.ma/fmvdjmur!
- 2 replies
Post
2399
Huge new bio datasets just dropped!!!
Check out them out @
ginkgo-datapoints
Read the blog for more info: https://huggingface.co/blog/cgeorgiaw/gdp
Check out them out @
ginkgo-datapoints
Read the blog for more info: https://huggingface.co/blog/cgeorgiaw/gdp
albertvillanova
posted
an
update
4 days ago
Post
1376
🚀 SmolAgents v1.19.0 is live!
This release brings major improvements to agent flexibility, UI usability, streaming architecture, and developer experience: making it easier than ever to build smart, interactive AI agents. Here's what's new:
🔧 Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency
🖥️ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.
🔄 Streaming Refactor
- Streaming event aggregation moved off the Model class
- ➡️ Better architecture & maintainability
📦 Output Tracking
- CodeAgent outputs are now stored in ActionStep
- ✅ More visibility and structure to agent decisions
🐛 Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching
📚 Docs Improvements
- Added quickstart examples with tool usage
- One-click Colab launch buttons
- Expanded reference docs (AgentMemory, GradioUI docstrings)
- Fixed broken links and migrated to .md format
🔗 Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0
💬 Try it out, explore the new features, and let us know what you build!
#smolagents #opensource #AIagents #LLM #HuggingFace
This release brings major improvements to agent flexibility, UI usability, streaming architecture, and developer experience: making it easier than ever to build smart, interactive AI agents. Here's what's new:
🔧 Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency
🖥️ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.
🔄 Streaming Refactor
- Streaming event aggregation moved off the Model class
- ➡️ Better architecture & maintainability
📦 Output Tracking
- CodeAgent outputs are now stored in ActionStep
- ✅ More visibility and structure to agent decisions
🐛 Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching
📚 Docs Improvements
- Added quickstart examples with tool usage
- One-click Colab launch buttons
- Expanded reference docs (AgentMemory, GradioUI docstrings)
- Fixed broken links and migrated to .md format
🔗 Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0
💬 Try it out, explore the new features, and let us know what you build!
#smolagents #opensource #AIagents #LLM #HuggingFace
Post
507
we've merged LightGlue keypoint matcher to Hugging Face transformers! it allows commercial use when paired with an open-source keypoint detector 🙏🏻
it works very well, try it yourself: ETH-CVG/LightGlue
here's an in-the-wild test with two images of the same place ⤵️
it works very well, try it yourself: ETH-CVG/LightGlue
here's an in-the-wild test with two images of the same place ⤵️
- 1 reply
cfahlgren1
posted
an
update
4 days ago
Post
202
I ran the Anthropic Misalignment Framework for a few top models and added it to a dataset:
cfahlgren1/anthropic-agentic-misalignment-results
You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!
You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!
sergiopaniego
posted
an
update
4 days ago
Post
316
One of my favorite perks of the Hugging Face Pro plan: ✨Dev mode✨
Connect your HF Space to VS Code and just build — with hot reload out of the box.
Game changer for fast prototyping. 💻
Google Colab made AI accessible. Now HF Spaces are doing it too! 😍
💡 New Hugging Face pricing: http://hf.co/pricing
💡 More details: https://huggingface.co/learn/cookbook/en/enterprise_cookbook_dev_spaces
Connect your HF Space to VS Code and just build — with hot reload out of the box.
Game changer for fast prototyping. 💻
Google Colab made AI accessible. Now HF Spaces are doing it too! 😍
💡 New Hugging Face pricing: http://hf.co/pricing
💡 More details: https://huggingface.co/learn/cookbook/en/enterprise_cookbook_dev_spaces
Post
4222
Release picks of the past week is here! Find more models, datasets, Spaces here
merve/june-20-releases-68594824d1f4dfa61aee3433
🖼️ VLMs/OCR
> moonshotai/Kimi-VL-A3B-Thinking-2506 is a powerful reasoning vision LM, 3B active params, smarter with less tokens, supports long documents, videos 👏 (OS)
> nanonets/Nanonets-OCR-s is 3.75B params OCR model based on Qwen2.5VL-3B-Instruct (OS)
💬 LLMs
> moonshotai/Kimi-Dev-72B is a strong coding model based on Qwen2.5-72B (OS)
> Mistral released mistralai/Mistral-Small-3.2-24B-Instruct-2506, an update to their former model with better function calling & instruction following (OS)
🗣️ Audio
> Google released google/magenta-realtime, real time music generation & audio synthesis (cc-by-4)
> kyutai released new speech-to-text models that come in 1B & 2B ( kyutai/stt-1b-en_fr, stt-2b-en_fr) with 0.5s and 2.5s delay
3D
> Tencent released tencent/Hunyuan3D-2.1 an image-to-3D model (see below)
🖼️ VLMs/OCR
> moonshotai/Kimi-VL-A3B-Thinking-2506 is a powerful reasoning vision LM, 3B active params, smarter with less tokens, supports long documents, videos 👏 (OS)
> nanonets/Nanonets-OCR-s is 3.75B params OCR model based on Qwen2.5VL-3B-Instruct (OS)
💬 LLMs
> moonshotai/Kimi-Dev-72B is a strong coding model based on Qwen2.5-72B (OS)
> Mistral released mistralai/Mistral-Small-3.2-24B-Instruct-2506, an update to their former model with better function calling & instruction following (OS)
🗣️ Audio
> Google released google/magenta-realtime, real time music generation & audio synthesis (cc-by-4)
> kyutai released new speech-to-text models that come in 1B & 2B ( kyutai/stt-1b-en_fr, stt-2b-en_fr) with 0.5s and 2.5s delay
3D
> Tencent released tencent/Hunyuan3D-2.1 an image-to-3D model (see below)
Post
238
Skywork-SWE 🔥 New code agent model by Skywork 天工
Skywork/Skywork-SWE-32B
✨ 32B - Apache 2.0
✨ 38.0% pass@1 on SWE-bench Verified
✨ Up to 47.0% with test-time scaling
✨ Shows clear data scaling law (8K+ demos)
✨ Built on Qwen2.5-Coder-32B + OpenHands
Skywork/Skywork-SWE-32B
✨ 32B - Apache 2.0
✨ 38.0% pass@1 on SWE-bench Verified
✨ Up to 47.0% with test-time scaling
✨ Shows clear data scaling law (8K+ demos)
✨ Built on Qwen2.5-Coder-32B + OpenHands